SUBSCRIBE TO OUR FREE NEWSLETTER
Daily news & progressive opinion—funded by the people, not the corporations—delivered straight to your inbox.
5
#000000
#FFFFFF
5
#000000
#FFFFFF
disinformation
AI Utopia, AI Apocalypse, and AI Reality
If we can’t build an equitable, sustainable society on our own, it’s pointless to hope that a machine that can’t think straight will do it for us.
Jul 06, 2025
Recent articles and books about artificial intelligence offer images of the future that align like iron filings around two magnetic poles—utopia and apocalypse.
On one hand, AI is said to be leading us toward a perfect future of ease, health, and broadened understanding. We, aided by our machines and their large language models (LLMs), will know virtually everything and make all the right choices to usher in a permanent era of enlightenment and plenty. On the other hand, AI is poised to thrust us into a future of unemployment, environmental destruction, and delusion. Our machines will gobble scarce resources while churning out disinformation and making deadly weapons that AI agents will use to wipe us out once we’re of no further use to them.
Utopia and apocalypse have long exerted powerful pulls on human imagination and behavior. (My first book, published in 1989 and updated in 1995, was Memories and Visions of Paradise: Exploring the Universal Myth of a Lost Golden Age; it examined the history and meaning of the utopian archetype.) New technologies tend to energize these two polar attractors in our collective psyche because toolmaking and language are humanity’s two superpowers, which have enabled our species to take over the world, while also bringing us to a point of existential peril. New technologies increase some people’s power over nature and other people, producing benefits that, mentally extrapolated forward in time, encourage expectations of a grand future. But new technologies also come with costs (resource depletion, pollution, increased economic inequality, accidents, and misuse) that evoke fears of an ultimate reckoning. Language supercharges our toolmaking talent by enabling us to learn from others; it is also the vehicle for formulating and expressing our hopes and fears. AI, because it is both technological and linguistic, and because it is being adopted at a frantic pace and so disruptively, is especially prone to triggering the utopia-apocalypse reflex.
Messages about both the promise and the peril of AI are often crafted by powerful people seeking to consolidate their control over the AI industry.
We humans have been ambivalent about technology at least since our adoption of writing. Tools enable us to steal fire from the gods, like the mythical Prometheus, whom the gods punished with eternal torment; they are the wings of Icarus, who flies too close to the sun and falls to his death. AI promises to make technology autonomously intelligent, thus calling to mind still another cautionary tale, “The Sorcerer’s Apprentice.”
What could go right—or wrong? After summarizing both the utopian and apocalyptic visions for AI, I’ll explore two questions: first, how do these extreme visions help or mislead us in our attempts to understand AI? And second, whom do these visions serve? As we’ll see, there are some early hints of AI’s ultimate limits, which suggest a future that doesn’t align well with many of the highest hopes or deepest fears for the new technology.
AI Utopia
As a writer, I generally don’t deliberately use AI. Nevertheless, in researching this article, I couldn’t resist asking Google’s free AI Overview, “What is the utopian vision for AI?” This came back a fraction of a second later:
The utopian vision for AI envisions a future where AI seamlessly integrates into human life, boosting productivity, innovation, and overall well-being. It’s a world where AI solves complex problems like climate change and disease, and helps humanity achieve new heights.
Google Overview’s first sentence needs editing to remove verbal redundancy (vision, envisions), but AI does succeed in cobbling together a serviceable summary of its promoters’ dreams.
The same message is on display in longer form in the article “Visions of AI Utopia” by Future Sight Echo, who informs us that AI will soften the impacts of economic inequality by delivering resources more efficiently and “in a way that is dynamic and able to adapt instantly to new information and circumstances.” Increased efficiency will also reduce humanity’s impact on the environment by minimizing energy requirements and waste of all kinds.
But that’s only the start. Education, creativity, health and longevity, translation and cultural understanding, companionship and care, governance and legal representation—all will be revolutionized by AI.
There is abundant evidence that people with money share these hopes for AI. The hottest stocks on Wall Street (notably Nvidia) are AI-related, as are many of the corporations that contribute significantly to the NPR station I listen to in Northern California, thereby gaining naming rights at the top of the hour.
Capital is being shoveled in the general direction of AI so rapidly (roughly $300 billion just this year, in the U.S. alone) that, if its advertised potential is even half believable, we should all rest assured that most human problems will soon vanish.
Or will they?
AI Apocalypse
Strangely, when I initially asked Google’s AI, “What is the vision for AI apocalypse?”, its response was, “An AI Overview is not available for this search.” Maybe I didn’t word my question well. Or perhaps AI sensed my hostility. Full disclosure: I’ve gone on record calling for AI to be banned immediately. (Later, AI Overview was more cooperative, offering a lengthy summary of “common themes in the vision of an AI apocalypse.”) My reason for proposing an AI ban is that AI gives us humans more power, via language and technology, than we already have; and that, collectively, we already have way too much power vis-à-vis the rest of nature. We’re overwhelming ecosystems through resource extraction and waste dumping to such a degree that, if current trends continue, wild nature may disappear by the end of the century. Further, the most powerful humans are increasingly overwhelming everyone else, both economically and militarily. Exerting our power more intelligently probably won’t help, because we’re already too smart for our own good. The last thing we should be doing is to cut language off from biology so that it can exist entirely in a simulated techno-universe.
Let’s be specific. What, exactly, could go wrong because of AI? For starters, AI could make some already bad things worse—in both nature and society.
Just as there are limits to fossil-fueled utopia, nuclear utopia, and perpetual-growth capitalist utopia, there are limits to AI utopia. By the same token, limits may prevent AI from becoming an all-powerful grim reaper.
There are many ways in which humanity is already destabilizing planetary environmental systems; climate change is the way that’s most often discussed. Through its massive energy demand, AI could accelerate climate change by generating more carbon emissions. According to the International Energy Agency, “Driven by AI use, the U.S. economy is set to consume more electricity in 2030 for processing data than for manufacturing all energy-intensive goods combined, including aluminum, steel, cement, and chemicals.” The world also faces worsening water shortages; AI needs vast amounts. Nature is already reeling from humanity’s accelerating rates of resource extraction and depletion. AI requires millions of tons of copper, steel, cement, and other raw materials, and suppliers are targeting Indigenous lands for new mines.
We already have plenty of social problems, too, headlined by worsening economic inequality. AI could widen the divide between rich and poor by replacing lower-skilled workers with machines while greatly increasing the wealth of those who control the technology. Many people worry that corporations have gained too much political influence; AI could accelerate this trend by making the gathering and processing of massive amounts of data on literally everyone cheaper and easier, and by facilitating the consolidation of monopolies. Unemployment is always a problem in capitalist societies, but AI threatens quickly to throw millions of white-collar workers off payrolls: Anthropic’s CEO Dario Amodei predicts that AI could eliminate half of entry-level white-collar jobs within five years, while Bill Gates forecasts that only three job fields will survive AI—energy, biology, and AI system programming.
However, the most horrific visions for AI go beyond just making bad things worse. The title of a recent episode of The Bulwark Podcast, “Will Sam Altman and His AI Kill Us All?”, states the worst-case scenario bluntly. But how, exactly, could AI kill us all? One way is by automating military decisions while making weapons cheaper and more lethal (a recent Brookings commentary was titled, “How Unchecked AI Could Trigger a Nuclear War”). Veering toward dystopian sci-fi, some AI philosophers opine that the technology, once it’s significantly smarter than people, might come to view biological humans as pointless wasters of resources that machines could use more efficiently. At that point, AI could pursue multiple pathways to terminate humanity.
AI Reality
I don’t know the details of how AI will unfold in the months and years to come. But the same could be said for AI industry leaders. They certainly understand the technology better than I do, but their AI forecasts may miss a crucial factor. You see, I’ve trained myself over the years to look for limits in resources, energy, materials, and social systems. Most people who work in the fields of finance and technology tend to ignore limits, or even to believe that there are none. This leads them to absurdities, such as Elon Musk’s expectation of colonizing Mars. Earth is finite, humans will be confined to this planet forever, and therefore lots of things we can imagine doing just won’t happen. I would argue that discussions about AI’s promise and peril need a dose of limits awareness.
Arvind Narayanan and Sayash Kapoor, in an essay titled “AI Is Normal Technology,” offer some of that awareness. They argue that AI development will be constrained by the speed of human organizational and institutional change and by “hard limits to the speed of knowledge acquisition because of the social costs of experimentation.” However, the authors do not take the position that, because of these limits, AI will have only minor impacts on society; they see it as an amplifier of systemic risks.
In addition to the social limits Narayanan and Kapoor discuss, there will also (as mentioned above) be environmental limits to the energy, water, and materials that AI needs, a subject explored at a recent conference.
AI seems to present a spectacular new slate of opportunities and threats. But, in essence, much of what was true before AI remains so now.
Finally, there’s a crucial limit to AI development that’s inherent in the technology itself. Large language models need vast amounts of high-quality data. However, as more information workers are replaced by AI, or start using AI to help generate content (both trends are accelerating), more of the data available to AI will be AI-generated rather than being produced by experienced researchers who are constantly checking it against the real world. Which means AI could become trapped in a cycle of declining information quality. Tech insiders call this “AI model collapse,” and there’s no realistic plan to stop it. AI itself can’t help.
In his article “Some Signs of AI Model Collapse Begin to Reveal Themselves,” Steven J. Vaughan-Nichols argues that this is already happening. There have been widely reported instances of AI inadvertently generating fake scientific research documents. The Chicago Sun-Times recently published a “Best of Summer” feature that included forthcoming novels that don’t exist. And the Trump administration’s widely heralded “Make America Healthy Again” report included citations (evidently AI-generated) for non-existent studies. Most of us have come to expect that new technologies will have bugs that engineers will gradually remove or work around, resulting in improved performance. With AI, errors and hallucination problems may just get worse, in a cascading crescendo.
Just as there are limits to fossil-fueled utopia, nuclear utopia, and perpetual-growth capitalist utopia, there are limits to AI utopia. By the same token, limits may prevent AI from becoming an all-powerful grim reaper.
What will be the real future of AI? Here’s a broad-brush prediction (details are currently unavailable due to my failure to upgrade my crystal ball’s operating system). Over the next few years, corporations and governments will continue quickly to invest in AI, driven by its ability to cut labor costs. We will become systemically dependent on the technology. AI will reshape society—employment, daily life, knowledge production, education, and wealth distribution. Then, speeding up as it goes, AI will degenerate into a hallucinating, blithering cacophony of little voices spewing nonsense. Real companies, institutions, and households will suffer as a result. Then, we’ll either figure out how to live without AI, or confine it to relatively limited tasks and data sets. America got a small foretaste of this future recently, when Musk-led DOGE fired tens of thousands of federal workers with the expectation of replacing many of them with AI—without knowing whether AI could do their jobs (oops: Thousands are being rehired).
A messy neither-this-nor-that future is not what you’d expect if you spend time reading documents like “AI 2027,” five industry insiders’ detailed speculative narrative of the imminent AI future, which allows readers to choose the story’s ending. Option A, “slowdown,” leads to a future in which AI is merely an obedient, super-competent helper; while in option B, “race,” humanity is extinguished by an AI-deployed bioweapon because people take up land that could be better used for more data centers. Again, we see the persistent, binary utopia-or-apocalypse stereotype, here presented with impressive (though misleading) specificity.
At the start of this article, I attributed AI utopia-apocalypse discourse to a deep-seated tic in our collective human unconscious. But there’s probably more going on here. In her recent book Empire of AI, tech journalist Karen Hao traces polarized AI visions back to the founding of OpenAI by Sam Altman and Elon Musk. Both were, by turns, dreamers and doomers. Their consistent message: We (i.e., Altman, Musk, and their peers) are the only ones who can be trusted to shepherd the process of AI development, including its regulation, because we’re the only ones who understand the technology. Hao makes the point that messages about both the promise and the peril of AI are often crafted by powerful people seeking to consolidate their control over the AI industry.
Utopia and apocalypse feature prominently in the rhetoric of all cults. It’s no surprise, but still a bit of a revelation, therefore, to hear Hao conclude in a podcast interview that AI is a cult (if it walks, quacks, and swims like a cult... ). And we are all being swept up in it.
So, how should we think about AI in a non-cultish way? In his article, “We Need to Stop Pretending AI Is Intelligent,” Guillaume Thierry, a professor of cognitive neuroscience, writes, “We must stop giving AI human traits.” Machines, even apparently smart ones, are not humans—full stop. Treating them as if they are human will bring dehumanizing results for real, flesh-and-blood people.
The collapse of civilization won’t be AI generated. That’s because environmental-social decline was already happening without any help from LLMs. AI is merely adding a novel factor in humanity’s larger reckoning with limits. In the short run, the technology will further concentrate wealth. “Like empires of old,” writes Karen Hao, “the new empires of AI are amassing extraordinary riches across space and time at great expense to everyone else.” In the longer run, AI will deplete scarce resources faster.
If AI is unlikely to be the bringer of destruction, it’s just as unlikely to deliver heaven on Earth. Just last week I heard from a writer friend who used AI to improve her book proposal. The next day, I went to my doctor for a checkup, and he used AI to survey my vital signs and symptoms; I may experience better health maintenance as a result. That same day, I read a just-published Apple research paper that concludes LLMs cannot reason reliably. Clearly, AI can offer tangible benefits within some fields of human pursuit. But we are fooling ourselves if we assume that AI can do our thinking for us. If we can’t build an equitable, sustainable society on our own, it’s pointless to hope that a machine that can’t think straight will do it for us.
I’m not currently in the job market and therefore can afford to sit on the sidelines and cast judgment on AI. For many others, economic survival depends on adopting the new technology. Finding a personal modus vivendi with new tools that may have dangerous and destructive side effects on society is somewhat analogous to charting a sane and survivable daily path in a nation succumbing to authoritarian rule. We all want to avoid complicity in awful outcomes, while no one wants to be targeted or denied opportunity. Rhetorically connecting AI with dictatorial power makes sense: One of the most likely uses of the new technology will be for mass surveillance.
Maybe the best advice for people concerned about AI would be analogous to advice that democracy advocates are giving to people worried about the destruction of the social-governmental scaffolding that has long supported Americans’ freedoms and rights: Identify your circles of concern, influence, and control; scrutinize your sources of information and tangibly support those with the most accuracy and courage, and the least bias; and forge communitarian bonds with real people.
AI seems to present a spectacular new slate of opportunities and threats. But, in essence, much of what was true before AI remains so now. Human greed and desire for greater control over nature and other people may lead toward paths of short-term gain. But, if you want a good life when all’s said and done, learn to live well within limits. Live with honesty, modesty, and generosity. AI can’t help you with that.
Keep ReadingShow Less
Courage: A Letter to the Oberlin College Class of 2025
Whatever the causes, the world has gone haywire and in the years ahead all of us will need courage more than ever.
Jun 12, 2025
I don’t know much about the theory of courage. But I believe that it shows up when summoned from the depths of our loyalties and affections—doing work for which we’re willing to live and die.
Whatever the causes, the world has gone haywire and in the years ahead all of us will need courage more than ever. A few examples to make the point:
- Some tech bros—about your age—are dismantling the Federal government, painstakingly assembled over 235 years;
- Immigrants—some U.S. citizens—are being arrested and shipped to foreign prisons... without due process;
- The president says he “doesn’t know” whether he must uphold the Constitution—that he swore to “preserve, protect, and defend” 125 days ago;
- Billionaires and mega corporations are getting more tax cuts;
- People, young and old, are dying in Ukraine, Gaza, South Sudan;
- Last week others died in heat and storms in the Midwest;
- During this one hour, we will release the heat equivalent from 18,000 Hiroshima-size bombs to an already overheated Earth; and
- Mendacity and oligarchy are on the march; Truth—our stock in trade—is under assault.
Future generations will think us “deranged” in Amitav Ghosh’s words. Your job—our job—is to prove them wrong and make a better future than that in prospect. So, “What is it you plan to do with your one wild and precious life?” (Mary Oliver)
As you think it over, know that there is work for you to do—good work... and trouble to cause, what John Lewis called “necessary trouble.” But good work and necessary trouble always come with the courage to do it. With that in mind, a few observations:
- Get a life before you select a career... have a compass, not an itinerary... know whose side you are on;
- Stand for something that matters—and there is a great deal that matters;
- Be less certain of your certainties, but more clear about your values;
- Laugh at the human predicament and yourself... otherwise you’re just not taking things seriously enough;
- Pay attention to serendipity—those small chance occurrences, once defined as God’s way to remain anonymous;
- Be grateful always: You are the beneficiary of kindnesses, known and unknown;
- Remember that you are kin to all that has ever lived, is living, and by our forbearance will live; and
- In coming years, as you learn, in Rutger Bregman’s words, to “self-diminish,” become more kind, compassionate, and wise.
As for courage... remember the Lion in The Wizard of Oz walking down that yellow brick road looking for courage... only to find that the wizard was a phony and that he had courage all along, it was all around him and It’s all around you too and will come when you most need it. You will be surprised when you discover how much you can do in the years ahead, and there is not a moment to lose.
AND Congratulations, we’re very proud of you! Godspeed!
Keep ReadingShow Less
Defunding Truth: Trump’s Attack on NPR and the War on Independent Media
The attack on NPR is not incidental. It is part of a broader, systematic effort to hollow out the institutions that sustain a shared civic life.
May 30, 2025
On May 27, 2025, NPR and three of its member stations filed a federal lawsuit against President Donald Trump and senior administration officials, challenging the legality and constitutionality of a sweeping executive order that seeks to eliminate all federal funding for public media. The order, signed in secret on May 1 and titled “Ending Taxpayer Subsidization of Biased Media,” instructs federal agencies and the Corporation for Public Broadcasting to sever direct and indirect support for NPR and PBS.
The White House claims public broadcasters have become ideologically compromised—too progressive, too elite. But the lawsuit lays bare what this order truly represents: an act of retaliation against protected speech, an attempt to coerce editorial compliance through financial pressure, and a direct violation of the First Amendment and the Public Broadcasting Act of 1967.
This isn’t just a legal question. It’s a campaign to punish an institution for refusing to perform ideology—or worse, for refusing to perform for profit.
Calling NPR “left-wing” isn’t just a complaint—it’s a tactic. It frames the pursuit of truth as bias, and intellectual legitimacy as partisanship.
The attack on NPR is not incidental. It is part of a broader, systematic effort to hollow out the institutions that sustain a shared civic life. It arrives amid a sweeping retreat from democratic infrastructure, in a media environment already distorted by market forces and polarized spectacle. The point is not to shrink government, but to starve the parts of it that still serve public truth.
And when that truth is no longer institutionalized—when public media is stripped away—we are left with a brittle and binary media ecosystem. One pole is built on the commodification of dissent: branded, aestheticized resistance packaged for affirmation but divorced from redistribution. The other is built on grievance-fueled nationalism: disinformation-heavy, algorithmically weaponized, and driven by a hunger for cultural control.
To be clear: This is not a critique of independent movement journalism, which continues to speak truth to power. The critique is directed at large-scale, corporate liberal media that simulates transformation while avoiding structural change. Between that and right-wing propaganda lies a collapsing middle—where nuance, contradiction, and collective understanding once lived.
Over the past decade, American institutions have developed a method of control that depends not on silencing dissent, but absorbing it. Dissent becomes aestheticized. A movement becomes a marketing slogan. A crisis becomes a campaign. Moral performance replaces material change. The result is a politics of gesture—rhetorically progressive, materially stagnant.
This logic has reshaped journalism itself. Newsrooms adopt the language of equity while preserving internal hierarchies. Social platforms reward provocation, not precision. Engagement becomes the end goal. As backlash rises, even institutions that once embraced equity quietly retreat—rewriting mission statements, cutting DEI staff, and recasting structural critique as reputational risk.
In this context, public media has held a distinct line. NPR hasn’t turned itself into a lifestyle brand. It hasn’t gamified its coverage or collapsed journalism into performance. Its reporting focuses on infrastructure—housing, public health, rural economies—topics long abandoned by commercial outlets because they don’t scale.
What’s at stake isn’t just funding—it’s whether journalism can still exist as a civic discipline rather than a partisan weapon or a market product.
And yes, it has a tone. That tone reflects a commitment to method, verification, and proximity to academic and professional norms. That is precisely what’s under attack. Calling NPR “left-wing” isn’t just a complaint—it’s a tactic. It frames the pursuit of truth as bias, and intellectual legitimacy as partisanship. The same campaign now targeting NPR has already targeted public universities, climate science, and historical scholarship.
This executive order wasn’t born of fiscal conservatism. It came from a worldview where facts are threats unless they’re profitable or loyal. On the surface, this is about money. Beneath it lies a deeper question: Can democracy survive without institutions committed to unmonetized, unmanipulated truth?
Public media is one of the last places where journalism operates outside of market logic. If it falls, we’re left with only two choices: branded content that performs outrage for engagement, or weaponized narrative designed to dominate. In that void, journalism becomes either commercialized or coerced.
We’re already living in the early stages of that collapse. Local papers are gone. Regional reporting has been gutted. What remains is a patchwork of influencers and platforms, each calibrated to a target audience, each echoing a self-reinforcing narrative.
Public media’s refusal to conform—to accelerate, to provoke, to monetize—is now treated not as moderation, but as provocation.
The lawsuit NPR has filed is necessary. But it also marks a threshold. What’s at stake isn’t just funding—it’s whether journalism can still exist as a civic discipline rather than a partisan weapon or a market product.
Public media is quiet. It’s moderate. It rarely declares. But in a media economy built on spectacle and churn, quietness itself has become an act of resistance.
The attack on NPR is not just political retaliation. It is a warning. It shows how intolerable independent institutions have become in a country where truth is measured by allegiance and journalism is judged by its usefulness to power.
The refusal to commodify dissent, the refusal to monetize distrust, is no longer just a professional standard. It is a political act.
And in a democracy increasingly organized around spectacle, that act may be the last thing keeping the lights on.
The revolution, Gil Scott-Heron once wrote, would not be televised. If NPR falls, it will not be broadcast at all. Not because no one is speaking—but because the signal has been cut.
Keep ReadingShow Less
Most Popular